AI Automation Engineer

Indsafri; South Africa; On-site; ZAR 900,000 - 1,200,000; Full time

Job summary

Indsafri is seeking an AI Automation Engineer to join its AI Payments Engineering Team. You will design and deliver AI-native automation for critical payments processes, focusing on reconciliations, audits, and incident automation, while ensuring compliance and auditable governance.

Role requires expertise in LLM orchestration, multi-agent systems, and production-grade workflows using n8n, MCP, and Claude/Anthropic APIs.

Qualifications

• Experience with LLM orchestration in high-stakes environments.
• Knowledge of AI failure modes in critical systems.
• Proficiency with Spring AI and Python orchestration.
• Experience with workflow engines such as n8n.
• Familiarity with AI APIs like Claude/Anthropic.
• Ability to deliver full lifecycle: discovery → design → build → deploy → optimize.
• Strong architectural thinking for scalable platforms.
• Ability to operate in fast-paced, ambiguous environments.
• Strong ownership mindset with a bias for execution.
• Bridge business and engineering domains.

Responsibilities

• Design and deploy production-grade AI automation workflows for critical payments processes including Reconciliations, Audit & reporting preparation, and Financial analytics.
• Utilize modern AI tooling such as Claude/Anthropic APIs, Java (Spring AI)/Python for orchestration, n8n (or equivalent workflow engines), and MCP or similar multi-agent coordination layers.
• Integrate internal and external systems through APIs, data pipelines, and reporting systems.
• Identify and implement automation opportunities across Payments operations to reduce manual effort.
• Maintain human oversight and approval controls where necessary to ensure accuracy and compliance.
• Ensure all workflows are production-ready, auditable, and compliant with regulatory requirements.
• Implement AI Governance & Risk Management principles, including classifying automation by risk tier and ensuring solutions include named process owners, documented data flows, access controls, and full audit logging.
• Design automation solutions that preserve control integrity in regulated environments.
• Develop reusable frameworks, templates, and workflows, along with documentation and standards, to facilitate scalable adoption.
• Build dashboards and metrics to track efficiency gains, cost reductions, risk outcomes, and ROI.
• Train Payments teams on the effective use of AI-enabled workflows and tools.

Skills

LLM orchestration

Multi-agent systems

AI failure modes

Business-Engineering bridging

Ownership mindset

Fast-paced environments

Execution bias

Tools

n8n

MCP

Spring AI

Python

Claude/Anthropic API

Job description

We are seeking a skilled AI Automation Engineer to join our pioneering AI Payments Engineering Team. This role is instrumental in designing and delivering an AI-native Payments Operating System, transforming high-effort financial operations through intelligent automation. You will leverage AI engineering, payments domain expertise, and production automation to create scalable, auditable, and efficient systems, focusing on critical processes like reconciliations, audits, and incident automation, ensuring both efficiency and control integrity.

Key Responsibilities:

• Design and deploy production-grade AI automation workflows for critical payments processes including Reconciliations, Audit & reporting preparation, and Financial analytics.
• Utilize modern AI tooling such as Claude/Anthropic APIs, Java (Spring AI)/Python for orchestration, n8n (or equivalent workflow engines), and MCP or similar multi-agent coordination layers.
• Integrate internal and external systems through APIs, data pipelines, and reporting systems.
• Identify and implement automation opportunities across Payments operations to reduce manual effort.
• Maintain human oversight and approval controls where necessary to ensure accuracy and compliance.
• Ensure all workflows are production-ready, auditable, and compliant with regulatory requirements.
• Implement AI Governance & Risk Management principles, including classifying automation by risk tier and ensuring solutions include named process owners, documented data flows, access controls, and full audit logging.
• Design automation solutions that preserve control integrity in regulated environments.
• Develop reusable frameworks, templates, and workflows, along with documentation and standards, to facilitate scalable adoption.
• Build dashboards and metrics to track efficiency gains, cost reductions, risk outcomes, and ROI.
• Train Payments teams on the effective use of AI-enabled workflows and tools.

Required Skills and Qualifications:

• Strong understanding of LLM orchestration and multi-agent systems.
• Knowledge of AI failure modes in high-stakes environments.
• Proficiency in Spring AI/Python-based orchestration.
• Experience with workflow engines (e.g., n8n or equivalent).
• Familiarity with AI APIs (e.g., Anthropic/Claude or similar).
• Ability to deliver solutions across the entire lifecycle: Discovery → Design → Build → Deploy → Optimize.
• Strong architectural thinking for scalable and future-ready platforms.
• Proven ability to operate effectively in fast-paced, ambiguous environments.
• Strong ownership mindset with a bias for execution.
• Ability to bridge business and engineering domains.

Preferred Qualifications:

• Experience with MCP or similar multi-agent coordination layers.
• Familiarity with payments domain specific processes (e.g., least cost routing, reconciliations).
• Experience with data pipelines and reporting systems.

Skills

Data Pipelines architectural design AI Automation Ownership mindset Multi-Agent Systems Reporting Systems AI Engineering Financial Analytics LLM Orchestration Payments Domain Expertise Production Automation Efficient Systems Auditable Systems Scalable Systems Reconciliation Automation Audit Automation Incident Automation Java (Spring AI) MCP (Multi-Agent Coordination Layers) Claude/Anthropic APIs Python Orchestration APIs Integration n8n (Workflow Engines) Automation Opportunity Identification Dashboards & Metrics AI Governance & Risk Management Control Integrity Reusable Frameworks & Templates AI Failure Mode Analysis Full Lifecycle Solution Delivery ROI Tracking AI-enabled Workflow Training Fast-paced Environment Adaptability Payments Specific Processes (Least Cost Routing, Reconciliations) Business-Engineering Bridging